C. Purcaru, R. Precup, D. Iercan, L. Fedorovici, B. Dohangie, Florin Dragan
{"title":"在未知室内环境中使用交通标志的非机器人移动机器人导航","authors":"C. Purcaru, R. Precup, D. Iercan, L. Fedorovici, B. Dohangie, Florin Dragan","doi":"10.1109/SACI.2013.6608982","DOIUrl":null,"url":null,"abstract":"This paper proposes a navigation algorithm that allows mobile robots that participate in different missions to move in unknown environment. The algorithm uses data from the sonar or from the infrared sensors mounted on the robots and data from the video camera with which the robots are equipped. Using the video camera the robots will be able to detect and classify different traffic signs that can help the robots to arrive the target points safely and in a short time. The algorithm includes a convolutional neural network with six layers to classify the traffic signs. Several simulations were run on the nRobotic platform developed at the “Politehnica” University of Timisoara, Romania, to validate the new algorithm. The simulation scenarios illustrate attractive mechatronics applications concerning the behaviors of robots in unknown environments in the presence of multiple traffic signs.","PeriodicalId":304729,"journal":{"name":"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Nrobotic mobile robot navigation using traffic signs in unknown indoor environments\",\"authors\":\"C. Purcaru, R. Precup, D. Iercan, L. Fedorovici, B. Dohangie, Florin Dragan\",\"doi\":\"10.1109/SACI.2013.6608982\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a navigation algorithm that allows mobile robots that participate in different missions to move in unknown environment. The algorithm uses data from the sonar or from the infrared sensors mounted on the robots and data from the video camera with which the robots are equipped. Using the video camera the robots will be able to detect and classify different traffic signs that can help the robots to arrive the target points safely and in a short time. The algorithm includes a convolutional neural network with six layers to classify the traffic signs. Several simulations were run on the nRobotic platform developed at the “Politehnica” University of Timisoara, Romania, to validate the new algorithm. The simulation scenarios illustrate attractive mechatronics applications concerning the behaviors of robots in unknown environments in the presence of multiple traffic signs.\",\"PeriodicalId\":304729,\"journal\":{\"name\":\"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2013.6608982\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2013.6608982","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nrobotic mobile robot navigation using traffic signs in unknown indoor environments
This paper proposes a navigation algorithm that allows mobile robots that participate in different missions to move in unknown environment. The algorithm uses data from the sonar or from the infrared sensors mounted on the robots and data from the video camera with which the robots are equipped. Using the video camera the robots will be able to detect and classify different traffic signs that can help the robots to arrive the target points safely and in a short time. The algorithm includes a convolutional neural network with six layers to classify the traffic signs. Several simulations were run on the nRobotic platform developed at the “Politehnica” University of Timisoara, Romania, to validate the new algorithm. The simulation scenarios illustrate attractive mechatronics applications concerning the behaviors of robots in unknown environments in the presence of multiple traffic signs.